2692-2967ISSN (Online)
2770-0216ISSN (Print)
Volume 14 , Issue 1 , PP: 23-30, 2026 | Cite this article as | XML | Html | PDF | Full Length Article
Nam Tatyana Gennadievna 1 *
Doi: https://doi.org/10.54216/AJBOR.140105
Interactive methods are increasingly used in higher education to improve engagement and learning outcomes; however, universities often lack a reproducible procedure for selecting methods, sequencing them within a class, and evaluating effectiveness with comparable indicators. This research article develops and reports an IMRaD‑aligned framework for integrating interactive methods into university classes and provides an empirical evaluation protocol that can be implemented in practice. The study uses a mixed design: (i) a structured literature synthesis on active learning, cognitive engagement, and instructional design, and (ii) a quasi‑experimental classroom evaluation protocol (recommended for adoption) combining observation, short surveys, and learning analytics from digital tools (polling/quizzes, interactive whiteboard logs, and learning management systems). Results are presented as an operational toolkit: a taxonomy of interactive methods and didactic functions, a method–outcome–motivation mapping, a standardized 90‑minute lesson architecture, implementation checklists, and a monitoring model with defined indicators for achievement, participation, and motivation. The discussion highlights how method coherence across lesson phases supports cognitive activity as a unity of perception, reasoning, and practice, and outlines limitations and future research using experimental designs. The article contributes practical instruments for evidence‑based teaching and offers a pathway for universities to move from descriptive claims about ‘interactivity’ to measurable improvement.
Interactive methods , Active learning , Higher education , Instructional design , Student motivation , Interactive whiteboard , Formative assessment , Learning analytics , Quasi-experiment
[1] C. C. Bonwell and J. A. Eison, Active Learning: Creating Excitement in the Classroom, ASHE-ERIC Higher Education Report No. 1. Washington, DC, USA, 1991.
[2] M. Prince, “Does active learning work? A review of the research,” J. Eng. Educ., vol. 93, no. 3, pp. 223–231, 2004.
[3] S. Freeman et al., “Active learning increases student performance in science, engineering, and mathematics,” Proc. Natl. Acad. Sci. USA, vol. 111, no. 23, pp. 8410–8415, 2014.
[4] J. Hattie, Visible Learning: A Synthesis of Over 800 Meta-Analyses Relating to Achievement. London, U.K.: Routledge, 2009.
[5] J. Biggs and C. Tang, Teaching for Quality Learning at University, 4th ed. Maidenhead, U.K.: Open Univ. Press, 2011.
[6] D. R. Garrison and H. Kanuka, “Blended learning: Uncovering its transformative potential in higher education,” Internet Higher Educ., vol. 7, no. 2, pp. 95–105, 2004.
[7] R. E. Mayer, Multimedia Learning, 2nd ed. Cambridge, U.K.: Cambridge Univ. Press, 2009.
[8] P. A. Kirschner, J. Sweller, and R. E. Clark, “Why minimal guidance during instruction does not work,” Educ. Psychol., vol. 41, no. 2, pp. 75–86, 2006.
[9] D. W. Johnson, R. T. Johnson, and K. A. Smith, “Cooperative learning returns to college,” Change, vol. 30, no. 4, pp. 26–35, 1998.
[10] E. L. Deci and R. M. Ryan, “The ‘what’ and ‘why’ of goal pursuits: Human needs and the self-determination of behavior,” Psychol. Inquiry, vol. 11, no. 4, pp. 227–268, 2000.
[11] P. R. Pintrich, “A motivational science perspective on the role of student motivation in learning and teaching contexts,” J. Educ. Psychol., vol. 95, no. 4, pp. 667–686, 2003.
[12] C. S. Dweck, Mindset: The New Psychology of Success. New York, NY, USA: Random House, 2006.
[13] P. Black and D. Wiliam, “Assessment and classroom learning,” Assess. Educ., vol. 5, no. 1, pp. 7–74, 1998.
[14] D. Wiliam, Embedded Formative Assessment. Bloomington, IN, USA: Solution Tree Press, 2011.
[15] M. T. H. Chi and R. Wylie, “The ICAP framework: Linking cognitive engagement to active learning outcomes,” Educ. Psychol., vol. 49, no. 4, pp. 219–243, 2014.
[16] J. Sweller, “Cognitive load during problem solving: Effects on learning,” Cogn. Sci., vol. 12, no. 2, pp. 257–285, 1988.
[17] B. S. Bloom, Taxonomy of Educational Objectives: The Classification of Educational Goals. London, U.K.: Longmans, 1956.
[18] L. W. Anderson and D. R. Krathwohl, Eds., A Taxonomy for Learning, Teaching, and Assessing. New York, NY, USA: Longman, 2001.
[19] L. S. Vygotsky, Mind in Society: The Development of Higher Psychological Processes. Cambridge, MA, USA: Harvard Univ. Press, 1978.
[20] Bandura, Self-Efficacy: The Exercise of Control. New York, NY, USA: Freeman, 1997.
[21] J. W. Creswell and J. D. Creswell, Research Design: Qualitative, Quantitative, and Mixed Methods Approaches, 5th ed. Thousand Oaks, CA, USA: SAGE, 2018.
[22] V. Slastenin, I. Isaev, and E. Shiyanov, Pedagogy. Moscow, Russia: Akademiya, 2002.
[23] E. M. Galishnikova, “Using an interactive whiteboard in the learning process,” Teacher, no. 4, pp. 8–10, 2007.
[24] G. K. Masharipova, “Effectiveness of using modern pedagogical technologies in teaching the course ‘Foundations of Spirituality,’” in Proc. Sci.-Pract. Conf., Tashkent, Uzbekistan, 2017, pp. 254–256.
[25] G. K. Masharipova and S. Ergashova, “The view of Eastern thinkers on youth education,” in Proc. Int. Conf. Research Innovations Multidisciplinary Sciences, 2021, pp. 336–338.
